Abstract
Mobile communication networks produce massive amounts of data which may be useful in identifying the location of an emergency situation and the area it affects. We propose a one pass clustering algorithm for quickly identifying anomalous data points. We evaluate this algorithm’s ability to detect outliers in a data set and describe how such an algorithm may be used as a component of an emergency response management system.
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This paper won the best student paper award at the North American Association for Computational and Organizational Science (NAACSOS) Conference 2006, University of Notre Dame, Notre Dame, IN, USA.
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Pawling, A., Chawla, N.V. & Madey, G. Anomaly detection in a mobile communication network. Comput Math Organiz Theor 13, 407–422 (2007). https://doi.org/10.1007/s10588-007-9018-7
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DOI: https://doi.org/10.1007/s10588-007-9018-7